The multiplexed detection of biomolecules plays an important role in clinical diagnostics, discovery, and basic science. This requires the ability to both encode substrates associated with specific biomolecule targets, and also to associate a detectable signal to the biomolecule target being quantified. For multiplexed assays, it is common to use functionalized substrates, planar or particle-based, to capture and quantify targets. In the case of particle-based multiplexed assays, each particle is functionalized with a probe that captures a specific target, and encoded for identification during analysis. In order to quantify the amount of target captured on a particle, a suitable labeling scheme is typically used to provide a measurable signal associated with the target. One class of molecules that is particularly challenging to quantify due to limitations with existing approaches to labeling is microRNA (miRNA).
miRNAs are short non-coding RNAs that mediate protein translation and are known to be dysregulated in diseases including diabetes, Alzheimer's, and cancer. With greater stability and predictive value than mRNA, this relatively small class of biomolecules has become increasingly important in disease diagnosis and prognosis. However, the sequence homology, wide range of abundance, and common secondary structures of miRNAs have complicated efforts to develop accurate, unbiased quantification techniques. Applications in the discovery and clinical fields require high-throughput processing, large coding libraries for multiplexed analysis, and the flexibility to develop custom assays. Microarray approaches provide high sensitivity and multiplexing capacity, but their low-throughput, complexity, and fixed design make them less than ideal for use in a clinical setting. PCR-based strategies suffer from similar throughput issues, require lengthy optimization for multiplexing, and are only semi-quantitative. Existing bead-based systems provide a high sample throughput (>100 samples per day), but with reduced sensitivity, dynamic range, and multiplexing capacities. Therefore, there is a need for improved methods for detecting and quantifying nucleic acids, such as, miRNA.
The multiplexed detection of miRNAs, or any other biomolecules requires the ability to encode a substrate associated with each. There are two broad classes of technologies used for multiplexing—planar arrays and suspension (particle-based) arrays, both of which have application-specific advantages. While planar arrays rely strictly on positional encoding, suspension arrays have utilized a great number of encoding schemes that can be classified as spectrometric, graphical, electronic, or physical.
Spectrometric encoding encompasses any scheme that relies on the use of specific wavelengths of light or radiation (including fluorophores, chromophores, photonic structures, or Raman tags) to identify a species. Fluorescence-encoded microbeads can be rapidly processed using conventional flow-cytometry (or on fiber-optic arrays), making them a popular platform for multiplexing. Most spectrometric encoding methods rely on the encapsulation of detectable entities for encoding, which can be very challenging depending on the substrate used. A more robust and generally-applicable encoding method is needed to enable rapid, universal encoding of substrates for multiplexed detection.